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TRANSCRIPT
Portfolio Workshop
University of Delaware Finance Lab Conference
R. Stafford Johnson Professor Department of Finance Xavier University
Objectives In this session, I want to cover some of the academic scholarship and teaching
subjects that comprise part of the finance discipline and show how I use Bloomberg in these areas.
I will draw from some of the Bloomberg exercises that are in Debt Markets and Analysis (Wiley) and in a forthcoming book, Equity Markets and Portfolio Analysis (Wiley).
I want to put some emphasis on portfolio analysis. Intent here is to show the breadth and debt of Bloomberg, as well as some of the
subtleties.
At the end, I hope to engage you in a discussion on how Bloomberg can be used in teaching finance and also in facilitating academic scholarship and research in finance.
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Finance Subjects • Stock Fundamental Analysis • Portfolio Parameters • Portfolio Theory, CAPM, and APT • Equity Style Investment • ETF Construction • Bond Evaluation
Total return analysis Equilibrium Bond Prices Level and Structure of interest rates Yield curve Bond spreads and risk
• Bond Portfolio Construction and Horizon Analysis • Swaps and “Off-balance Sheet” Portfolio Management • Derivatives • Research 3
Fundamental stock analysis • Multiplier (P/e) valuation model
• Relative evaluation of a stock’s growth rates and its
capitalization rate in terms of risk premium measures
• Model for estimating earnings-per-share
• Methods for estimating P/e
• Comparison of P/e with sector and market indexes.
4
Risk Premium Analysis
Financial Risk: Debt-to-earnings and debt-to-asset ratios
5
Stock
Analysis
Analysis of growth rates, risk premiums, and relative P/e ratios to determine the stock’s equilibrium P/e.
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• Inputs: Bloomberg’s sustainable growth rate = 4.4%; D/E = 0.5; Adjusted Beta = .708; expected market return = 9.5%; risk-free rate = 1.6%; discount rate = k = 7.2%.
86.17=044.-072.
50.=
g-kE/D
=EP 11
Stock
Analysis
Forecast of the company’s eps. Excel multiplier
program linked to Bloomberg.
Comparison of forecast with analysts’ forecast (Bloomberg ANR and EE).
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Stock
Analysis
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3/31/2011 6/30/2011 9/30/2011 12/31/2011 3/31/2012 6/30/2012 Trailing Next FQ1 2011 FQ2 2011 FQ3 2011 FQ4 2011 FQ1 2012 FQ2 2012 Four Quarters Full Year
12,573 13,878 13,226 14,688 13,093 13,286 54,293 53,207 -8.71% 10.38% -4.70% 11.05% -10.86% 1.47% 4.24% -2.00% 7,937 9,007 8,611 9,795 8,426 8,416 35,248 34,543
-11.57% 13.48% -4.40% 13.75% -13.98% -0.12% 5.34% -2.00% 63.13% 64.90% 65.11% 66.69% 64.36% 63.34% 64.92% 64.92%
2,990 3,065 2,924 3,386 2,878 2,907 12,095 11,805 -15.18% 2.51% -4.60% 15.80% -15.00% 1.01% -2.39% -2.40% 23.78% 22.09% 22.11% 23.05% 21.98% 21.88% 22.28% 22.19%
1,646 1,806 1,691 1,507 1,789 1,963 6,950 6,859 13.09% 13.01% 12.79% 10.26% 13.66% 14.78% 12.80% 12.89%
462 441 425 317 568 445 1,755 1,720 -13.64% -4.55% -3.63% -25.41% 79.18% -21.65% -6.20% -2.00%
- - - - - - - - (16) - (7) 256 83 68 400 -
1,200 1,365 1,273 934 1,138 1,450 4,795 5,139 398 389 346 92 319 416 1,173 -
33.17% 28.50% 27.18% 9.85% 28.03% 28.69% 24.46% 0.00% 802 976 927 842 819 1,034 3,622 5,139 - - - - - - - - - - - - - - - -
3 - 5 12 6 5 28 - 799 976 922 830 813 1,029 3,594 5,139
0.46 0.55 0.52 0.47 0.46 0.58 2.03 2.89
Revenue Sales Growth Cost of Goods Sold (Revenue) % ? in COGS COGS/Revenue Selling, General & Administrative Expense % ? in S,G,&A S,G,&A/Revenue Operating Income Operating Margin Interest Expense % ? in Interest Foreign Exchange Loss (G) Net Non-Operating Loss (G) Pretax Income Income Tax Expense Effective Tax Rate Income Before XO Items XO Loss (Gain) Pretax Tax Effect on XO Items Minority Interest Net Income EPS Number of Shares
Stock
Analysis
Analysts’ forecast: Bloomberg ANR and EE
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Stock Analysis
Determine the stock’s intrinsic value: V = (P/e)(E(eps). Determine if the stock is underpriced or overpriced.
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•P/E for Kraft: •Historical P/e = 16.73 •Recent P/e = 17.7 •Based on our estimated EPS of $2.89, the intrinsic values are:
•V = (16.73)($2.89) = $48.35 •V = (17.7)($2.89) = $51.15 •V = (17.86)($2.89) = $51.62
•Market Price = $41
•IV > PMkt
•Strong Buy
• Analysts’ estimate of EPS = $2.48 •V = (16.73)($2.48) = $41.49 •V = (17.7)($2.48) = $43.90 •V = (17.86)($2.49) = $44.47
•Market Price = $41
•IV > PMkt
•Weak Buy
Portfolio Parameters
Linear regressions for the Disney Corporation and General Electric
Both regressions were done on Bloomberg’s “Beta” screen.
In each regression, the stock’s daily percentage returns are regressed against the percentage changes in the S&P 500 (SPX) for the period from 5/1/06 to 4/28/11.
The Beta screen shows the scatter diagram, regression estimates, and qualifiers.
From this regression, Disney has a beta 1.067, alpha of .040, σ(ε) of 1.193 (V(ε) = 1.42325), t-statistic = β/ σ(β) = 50.04, and R2 of .6667.
GE has a beta 1.158, alpha of –.029, σ(ε) of 1.663 (V(ε) = 2.7656), t-statistic = β/ σ(β) = 38.941, and R2 of .547.
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Portfolio Parameters
PC Screen
The Bloomberg’s PC screen for GE compares
the R2’s, Betas, and alphas for GE and related companies in its industry.
Based on its R2, approximately 50% of GE’s variability is explained by market factors.
GE’s beta of 1.254 exceeds the beta of most of its peers, with the exception being Caterpillar and Abbot Labs.
GE is only one of two in the peer group with a negative alpha for the regression period analyzed.
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Portfolio Parameters, PC Screen
On the PC screen, the
Alphas and betas for each stock for the time period selected can be accessed from the “Calculation” tab and exported to Excel from the “Export” tab (upper right corner).
Each stock’s variance of the error, V(ε), can be calculated from the sock’s R2 and its variance (V(r) (V(ε) = V(r) (1 − R2)) using the stock variances, found by clicking “Covariance” in the “Calculation” tab, and R2’s found by clicking “R2” in the “Calculation” tab.
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Security Alpha Beta V(ri) R2 V(εi) = V(ri) (1 − R2)
WALT DISNEY 0.693 1.155 27.183 0.687 8.508
CVS CAREMARK CORP 0.592 0.786 18.498 0.366 11.728
KROGER CO 0.560 0.467 10.980 0.163 9.190
AFLAC INC 0.367 1.741 40.954 0.521 19.617
JOHNSON & JOHNSON 0.290 0.576 13.548 0.425 7.790
DUKE ENERGY CORP 0.288 0.362 8.520 0.202 6.799
EXXON MOBIL CORP 0.273 0.543 12.768 0.307 8.848
PROCTER & GAMBLE 0.216 0.459 10.797 0.251 8.087
MICROSOFT CORP 0.100 1.000 23.520 0.429 13.430
ARCHER-DANIELS-MIDLAND 0.028 0.421 9.909 0.057 9.344
S&P 500 INDEX 0.000 1.000 23.527 1.000 0.000
Data imported to Excel from PC
Monthly Data Period: 8/13/2006-8/13/2013
Portfolio
Parameters, CORR Screen
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A B C D E F G H I J K L M1 Security ADM AFL CVS DIS DUK JNJ KR MSFT PG XOM
2 ADM 20.196 9.934 3.544 8.107 4.019 4.302 4.729 3.963 3.704 7.784 0.305 0.53 AFL 9.934 36.156 6.196 14.156 7.065 6.165 5.717 9.161 5.948 8.274 6.805 0.54 CVS 3.544 6.196 11.732 5.032 3.182 1.918 3.318 4.012 2.137 3.883 8.455 0.55 DIS 8.107 14.156 5.032 14.588 4.8 4.761 4.537 6.853 5.07 7.048 9.890 0.56 DUK 4.019 7.065 3.182 4.8 6.893 3.398 3.205 3.987 3.003 4.069 3.785 0.57 JNJ 4.302 6.165 1.918 4.761 3.398 4.956 3.336 3.631 3.089 3.645 4.535 0.58 KR 4.729 5.717 3.318 4.537 3.205 3.336 11.191 3.761 3.034 4.07 7.885 0.59 MSFT 3.963 9.161 4.012 6.853 3.987 3.631 3.761 14.154 3.256 5.512 3.505 0.5
10 PG 3.704 5.948 2.137 5.07 3.003 3.089 3.034 3.256 5.804 3.597 3.495 0.511 XOM 7.784 8.274 3.883 7.048 4.069 3.645 4.07 5.512 3.597 9.418 2.590 0.512 0.610 13.610 16.910 19.780 7.570 9.070 15.770 7.010 6.990 5.180 0 013 1 1 1 1 1 1 1 1 1 1 0 01415 0.067012 -0.00553 0.012222 0.015548 -0.00541 -0.01789 0.007721 0.004388 -0.013705386 -0.064 -0.01632 0.13865316 -0.00553 0.046287 0.002585 -0.03075 -0.0123 0.001258 0.003457 -0.00746 0.002631718 -2E-04 -0.00205 -0.0579217 0.012222 0.002585 0.091248 -0.04336 -0.02618 -0.00096 -0.03186 -0.00355 0.003847209 -0.004 0.01559 0.0370418 A-1 0.015548 -0.03075 -0.04336 0.085151 0.025771 -0.03156 -0.03413 0.004424 0.005667658 0.0032 0.04174 -0.4407919 -0.00541 -0.0123 -0.02618 0.025771 0.249286 -0.1127 -0.00139 -0.01795 -0.055224029 -0.044 -0.0099 0.22831520 -0.01789 0.001258 -0.00096 -0.03156 -0.1127 0.386061 -0.05473 -0.02586 -0.124769043 -0.019 0.00605 0.36665721 0.007721 0.003457 -0.03186 -0.03413 -0.00139 -0.05473 0.102875 0.004441 -0.001792773 0.0054 0.02018 -0.1115122 0.004388 -0.00746 -0.00355 0.004424 -0.01795 -0.02586 0.004441 0.100509 -0.015192645 -0.044 -0.01116 0.12992223 -0.01371 0.002632 0.003847 0.005668 -0.05522 -0.12477 -0.00179 -0.01519 0.24940909 -0.051 -0.02365 0.5050624 -0.06436 -0.00018 -0.004 0.003244 -0.04389 -0.01885 0.005407 -0.04375 -0.050871799 0.2172 -0.02048 0.20457525 -0.03265 -0.00409 0.031186 0.083477 -0.0198 0.012103 0.040365 -0.02233 -0.04730571 -0.041 -0.04424 0.35884726 0.277306 -0.11584 0.07408 -0.88159 0.45663 0.733313 -0.22301 0.259844 1.010119194 0.4092 0.35885 -9.6754527 k W W W Cov28 0 -0.11436 w1 ADM 2.156376
29 0 -0.08965 w2 AFL 4.281346
30 0 0.278733 w3 CVS 4.820762
31 0 0.206157 w4 DIS 5.28989 W/ (W cov) = 4.5903 V(Rp)
32 0 0.074859 w5 DUK 3.294052
33 0 0.460455 = w6 JNJ 3.539241
34 0 0.201318 w7 KR 4.634418
35 0 -0.04313 w8 MSFT 3.202515
36 0 0.13844 w9 PG 3.199246
37 0 -0.11282 w10 XOM 2.903384
38 Ep* 15.5 -0.32692 λ1
39 1 -4.11333 λ2
4041 W/ -0.11436 -0.08965 0.278733 0.206157 0.074859 0.460455 0.201318 -0.04313 0.138440345 -0.113
Markowitz Efficient Portfolios Using the Bloomberg Asset Allocation Optimizer
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This application requires Excel's Solver Add-in to be installed. Go to Help tab for directions. You may also contact Bloomberg Help Desk.Asset Allocation Optimizer uses either historical returns or user-customized forecasted returns to generate optimal portfolios. Follow directions on the left side of the screen to start using the application. You may customize start and end dates for historical return, standard deviation, and corre
1) Enter Tickers ----> Tickers: Adm Equity AFL Equity CVS Equity Dis Equity Duk Equity JNJ Equity KR Equity MSFT Equity PG Equity XOM Equity
2) Enter Asset Class ----> Asset Class: ADM AFL CVS Dis Duke J&J Kroger Microsoft PG Exxon
ARCHER-DANIELS-
AFLAC INC CVS CAREMARK
WALT DISNEY CO/THE
DUKE ENERGY CORP
JOHNSON & JOHNSON
KROGER CO MICROSOFT CORP
PROCTER & GAMBLE
EXXON MOBIL CORP
3) Choose Return Type Returns * 0.61% 13.61% 16.91% 19.78% 7.57% 9.07% 15.77% 7.01% 6.99% 5.18%
Type 1: Standard Dev 32.5% 43.3% 24.7% 27.6% 18.5% 15.9% 24.2% 27.1% 17.3% 22.1%* For demonstration only; these are not recommendations; please review your inputs carefully.
ARCHER-DANIELS-
AFLAC INCCVS
CAREMARK WALT DISNEY
CO/THEDUKE ENERGY
CORPJOHNSON &
JOHNSONKROGER CO
MICROSOFT CORP
PROCTER & GAMBLE
EXXON MOBIL CORP
ARCHER-DANIELS
1.000
AFLAC INC 0.366 1.000
CVS CAREMARK CORP
0.231 0.300 1.000
WALT DISNEY CO/THE
0.471 0.615 0.389 1.000
DUKE ENERGY 0.347 0.438 0.357 0.481 1.000
4) Enter Dates Below JOHNSON & 0.431 0.458 0.254 0.560 0.589 1.000
Start Date: 8/5/2006 KROGER CO 0.314 0.279 0.290 0.350 0.369 0.444 1.000
End Date: 8/8/2013 MICROSOFT 0.233 0.400 0.311 0.477 0.401 0.433 0.298 1.000
PROCTER & GAMBLE
0.350 0.414 0.263 0.555 0.496 0.585 0.381 0.365 1.000
EXXON MOBIL CORP
0.564 0.444 0.374 0.604 0.506 0.542 0.395 0.478 0.498 1.000
5) Review Constraints ----> Min Weight 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Constraints Kept Max Weight 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0% 99.0%
6) Press Button - Optimize Objective 1: Portfolio that minimizes risk Risk Free Return: 1.50% Return: 9.80% Standard Dev: 13.8%
Weights 0.0% 0.0% 14.6% 0.0% 13.9% 38.6% 5.4% 0.2% 27.3% 0.0%
Objective 2: Portfolio that maximizes return Risk Free Return: 1.50% Return: 19.75% Standard Dev: 27.4%
Weights 0.0% 0.0% 1.0% 99.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Objective 3: Portfolio that maximizes Sharpe Ratio Risk Free Return: 1.50% Return: 17.47% Standard Dev: 19.1%
Weights 0.0% 0.0% 33.9% 33.1% 0.0% 0.3% 32.7% 0.0% 0.0% 0.0%
Objective 4: Portfolio that maximizes return (*given a volatility) Risk Free Return: 2.50% Return: 15.53% Standard Dev: 17.0%
Weights 0.0% 0.0% 31.1% 21.4% 0.0% 21.6% 26.0% 0.0% 0.0% 0.0%
Objective 5: Portfolio that minimizes risk (*given a return) Risk Free Return: 2.50% Return: 15.50% Standard Dev: 17.0%
Weights 0.0% 0.0% 30.7% 21.4% 0.0% 22.0% 25.9% 0.0% 0.0% 0.0%
Type 2:
You have chosen forecasted rates. Please go to the
Forecasted Rates Tab to review your return
assumptions.
Historical returns, correlations and standard
deviations will update according to dates chosen.
Asset Allocation Optimizer
Historical
Forecasted
Markowitz Efficient Portfolios Using the Bloomberg Asset Allocation Optimizer
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Risk Return ADM AFL CVS Dis Duke J&J Kroger Microsoft PG Exxon
13.8% 9.8% 0.0% 0.0% 14.6% 0.0% 13.9% 38.6% 5.4% 0.2% 27.3% 0.0%
13.9% 10.5% 0.0% 0.0% 18.3% 0.0% 10.2% 39.5% 9.2% 0.0% 22.8% 0.0%
14.1% 11.2% 0.0% 0.0% 22.2% 0.0% 6.4% 39.5% 13.1% 0.0% 18.8% 0.0%
14.4% 11.9% 0.0% 0.0% 24.4% 2.5% 4.2% 38.4% 15.3% 0.0% 15.1% 0.0%
14.8% 12.6% 0.0% 0.0% 25.6% 5.8% 2.1% 37.6% 17.5% 0.0% 11.4% 0.0%
15.3% 13.4% 0.0% 0.0% 27.4% 9.7% 0.0% 35.8% 19.5% 0.0% 7.7% 0.0%
15.8% 14.1% 0.0% 0.0% 28.3% 13.2% 0.0% 33.8% 21.8% 0.0% 2.9% 0.0%
16.3% 14.8% 0.0% 0.0% 29.7% 17.2% 0.0% 29.8% 23.2% 0.0% 0.0% 0.0%
17.0% 15.5% 0.0% 0.0% 30.7% 21.4% 0.0% 22.0% 25.9% 0.0% 0.0% 0.0%
17.7% 16.2% 0.0% 0.0% 31.9% 25.6% 0.0% 14.3% 28.2% 0.0% 0.0% 0.0%
18.5% 16.9% 0.0% 0.0% 33.1% 29.8% 0.0% 6.6% 30.4% 0.0% 0.0% 0.0%
19.3% 17.6% 0.0% 0.0% 33.4% 36.1% 0.0% 0.0% 30.4% 0.0% 0.0% 0.0%
20.9% 18.3% 0.0% 0.0% 28.3% 55.3% 0.0% 0.0% 16.4% 0.0% 0.0% 0.0%
23.5% 19.0% 0.0% 0.0% 23.2% 74.2% 0.0% 0.0% 2.6% 0.0% 0.0% 0.0%
27.4% 19.8% 0.0% 0.0% 1.0% 99.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0%
Ret
urn
Risk (Standard Deviation)
Efficient Frontier
ADM
AFL
CVS
Dis
Duke
J&J
Kroger
Microsoft
PG
Exxon
Ex-Post Performance, 8/13/2012-8/12/13
Markowitz Portfolio (Blue Rock Equity) and S&P 500
17
Bloomberg and Markowitz Excel Program Using Elton, Gruber, Padberg, and Manfred Technique for Determining Allocation
18
Rf 10 yr treasRm Index SPX
Start date 8/5/2006Ending date 8/8/2013Daily or weekly W
Beta Type raw betaRelativev Index SPXStart date 8/5/2006Ending date 8/8/2013Daily or weekly W
Import Data Type PortfolioID or Name u5945505-128
Name E(rj) βj V(εj) Rf V(RM) λβ Ci Wi
KROGER CO 15.77 0.56 8.70 2.58 2.84 23.73 2.1750 22.5%CVS CAREMARK CORP 16.91 0.61 8.71 2.58 2.84 23.44 4.2959 24.3%WALT DISNEY CO 19.78 1.08 5.08 2.58 2.84 15.99 8.3425 35.7%JOHNSON & JOHNSON 9.07 0.50 2.89 2.58 2.84 12.92 8.8792 16.6%DUKE ENERGY CORP 7.57 0.55 4.43 2.58 2.84 9.09 8.8967 0.5%PROCTER & GAMBLE CO 6.99 0.49 3.87 2.58 2.84 9.04 8.9068 0.4%AFLAC INC 13.61 1.51 17.61 2.58 2.84 7.33 8.7041 0.0%MICROSOFT CORP 7.01 0.80 8.98 2.58 2.84 5.56 8.4977 0.0%EXXON MOBIL CORP 5.15 0.78 4.45 2.58 2.84 3.30 7.9118 0.0%ARCHER-DANIELS-MIDLAND CO 0.61- 0.88 13.88 2.58 2.84 3.62- 7.4022 0.0%
Portfolio Insurance—OSA
The value of the XSIF portfolio on August 31, 2012 was $1,221,287
The S&P 500 closed at 1400, and December 1400 S&P 500 put option was trading at 59.70 ($100 multiplier) and December 1475 S&P 500 call was trading at 21.60.
Portfolio Insurance: np = $1,221,287/(1,400 x $100) = 8.72 Long Nine S&P 500 put contracts; Cost =
(9)(100)(59.70) = $53,730
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Portfolio Insurance
Range Forward Position
Market Timing
The value of the XSIF portfolio on August 31,
2012 was $1,221,287, the S&P 500 closed at 1,400, a December 1,400 S&P 500 put option was trading at 59.70 ($100 multiplier) and December 1,400 S&P 500 call was trading at 57.05.
Synthetic Long Position: Short: np = $1,221,287/(1,400 x $100) = 8.72 Long: nc = $1,221,287/(1,400 x $100) = 8.72 Cost = Cost = [(9)(100)(59.70)] − [(9)(100)(57.05)
= $34,290 = $2,385
For 20% plus and minus range in value, the portfolio’s profit and loss percentage ranges between −11.57% and +32.64%
For 20% plus and minus range in value, the option-enhanced portfolio’s profit and loss percentage ranges between −31.38% and +54.36%
20
Profit percentage graph without options
Profit percentage graph with options
Efficient Markets : Style Portfolio
Stocks with the potential for consistent earnings and dividend growth without high volatility:
Market Cap.: Greater than or Equal to $2.0B
P/E (TTM Intraday): Less than or Equal to 20
Book Value Growth (5-Yr Avg.): Greater than or Equal to 5%
EPS Growth: 5-Yr Hist.: Greater than or Equal to 10%
Ret. on Equity (TTM): Greater than or Equal to 20%
Beta: Less than or Equal to 1.25 Divd. Growth Rate (5-Yr Avg.): Greater
than or Equal to 5%
21
Efficient Markets
Style Portfolio
Stocks with the potential for consistent earnings and dividend growth without high volatility.
22
Bond Evaluation
Total Returns Equilibrium Bond Prices
Level and Structure of Rates Yield Curve Analysis
Bond Risk and Spreads
Total Return and Horizon Analysis—TRA
The TRA screen calculates total returns given different interest rate case.
The user can select different horizons, reinvestment rates (semiannual rate, S/A Reinv), and yield shifts (YLD SHFT).
The yield shifts are projected basis point shifts in the baseline yield curve (e.g. Treasury) between the settlement date and horizon date.
The screen shows the calculated price of the bond at the horizon at the yield reflecting the shift and the annualized total return based on the price, coupon, and interest on interest at the horizon and the current price.
24
Yield Curves
The IYC9 screen shows the
total returns for different horizons and yield curve shift scenarios.
The top screen shows the total returns for each maturity from buying a Treasury and selling it one year later given no change in rates. As the total return graph shows, the largest returns occur from the intermediate-term and long-term maturities.
25
Option Adjusted Spread Analysis—OAS1
Options adjusted spread (OAS) analysis is a method for value bonds with embedded options and estimating the additional spread required to compensate investors for the call risk they are assuming.
The OAS1 screen shows the calculated OAS and also the spread of the bond if there were no embedded options—the option-free spread. The spread due to embedded options can be estimated by subtracting the option-free spread from the total spread.
Using the Black-Derman-Toy model, the estimated an option-free spread for Ford on April 13, 2012 was 406.3 basis points. Given the total spread of 456.95 bp, the estimated spread due to Ford’s call option is 50.65 bp.
Note: Black-Derman Model has been
replaced in the updated OAS1 screen.
26
27
AZS: Bloomberg Altman Z-Score
Screen
The Bloomberg screen shows the Altman Z-score model applied to Kraft and Ford on 4/15/2012.
As shown, Kraft has a score of 3.20, placing it in the unlikely default category, and a relatively stable Z-score history.
In contrast, Ford has a Z-score of 0.87, placing it in the increased risk of failure category.
However, it Z-score history in which its score has increased from a low of –0.0384 in 3/31/09 to 0.87 on 4/15/2012 indicates a significant improvement in credit quality.
28
Constructing bond portfolios—PRTU
From the PMEN menu, some useful screens for analyzing fixed-income portfolios include: PORT: Portfolio & Risk Analytics; BSA: Scenario Analysis; PDSP: Portfolio Display; NPH: Portfolio News; CACT: Corporate Action Calendar; EVTS: Events Calendar; BSA: Scenario Analysis; PSH: Proposed Trade/Hedge Analysis; PCF: Expected Cash Flow; PREP; DRAM: Default Risk Monitor.
The PORT, BSA, EVTS, and DRAM screens that are shown in the following slides are for the Xavier Student Investment Fund (XSIF) bond portfolio as of September 29, 2012.
Bond Portfolios and Horizon Analysis PRTU and PMEN
29
PORT: Characteristics
30
BSA
Horizon Analysis
31
DRAM
DRAM: Default Risk Monitor
32
EVTS EVTS:
Events Calendar
33
Portfolio Duration and Horizon Analysis
Total Returns for Portfolio with Duration of 5.5 and Horizon of 6
34
Tab Screens: Details tab shows the detail of the
swap
Resets tab shows the reset rate at each effective date (forward LIBOR plus basis point you added to spread; one can change the rates from this tab).
Curves tab shows graphically the payments, receipts, and net payments. This tab screen can be adjusted to show each counterparty (pay fix or receive fix), cash flow, and market values.
Example: Fixed/Floating swap (Leg 1 is fixed-rate payer); NP = $5.75 million; fixed rate (coupon) = 1.5%; floating rate = 6-month LIBOR + 25 bp; frequency = semiannual; maturity = 5 years; forward curve = U.S. swaps (#23); discount curve = U.S. swaps (#23).
Bond Portfolios and Swaps SWPM
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MARS
Portfolio of five corporate bonds with market value of $5.75 million on 5/27/2012 and a generic five-year fixed payer swap with 1.5% fixed rate/LIBOR + 25 bp, NP = $5.75 million
Scenario: yield curve shifts: −100 bp to + 100 bp.
Market value evaluated currently and one year later
Analysis: Bond Portfolio only; Swap only; Combined portfolio and fixed payer swap
Options OSA: Bloomberg’s Option Scenario Screen Example: IBM 1. Click OSA 2. On the OSA screen, click the red “Positions” tab and
then click “Add Listed Options” to bring up options listed on the security. This bring up a screen showing the listed options from which to select
3. After selecting the positions, type 1 <Enter> to load positions and bring up the OSA position screen
4. On the position screen, click the grey “Scenario Chart” tab at the top of the screen to bring up the profit graph. The profit graph shows profits for the strategy at expiration where the option price is trading at its intrinsic value and also at times periods prior to expiration where the option price is determined by an option pricing model. The profit graphs for different periods can be changed or deleted by using the select options at the top of the screen.
5. From the position screen (click Position tab), one can select different positions and then click “Scenario Chart” tab to view the profit graph.
6. The “Scenario” screen (click grey “Scenario” tab) shows the profit table
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Bloomberg Option Pricing Screen—OV or OVME
The Bloomberg OV screen calculates the price of an option using the Black-Scholes OPM or the Binomial (Trinomial).
The user can input the variability or use the historical volatility or the implied variance.
The OV or OVME screen can be used to value exiting options or an option created from an existing security.
Example: IBM Call and Put
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Screens and Searches
Economic Information
Industry—BI
Excel—Linking Bloomberg data to your own programs; Bloomberg Excel programs
Event Analysis
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Back-Testing
Counties
Supply Chain and Input-Output
News and Law
Monitors
Launchpad
Facilitating Research—Some Thoughts